Short‐term load forecasting at electric vehicle charging sites using a multivariate multi‐step long short‐term memory: A case study from Finland-Reference-Cited by-同舟云学术

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Short‐term load forecasting at electric vehicle charging sites using a multivariate multi‐step long short‐term memory: A case study from Finland

Published:2021-06-11 Issue:4 Volume:11 Page:405-419
ISSN:2042-9738
Container-title:IET Electrical Systems in Transportation
language:en
Short-container-title:IET Electrical Systems in Transportation

Author:

Unterluggauer Tim¹²³^ORCID,Rauma Kalle²^ORCID,Järventausta Pertti¹,Rehtanz Christian²

Affiliation:

1. Unit of Electrical Engineering Tampere University Tampere Finland

2. Institute of Energy Systems Energy Efficiency and Energy Economics TU Dortmund University Dortmund Germany

3. Department of Electrical Engineering Technical University of Denmark Denmark

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/els2.12028

Reference40 articles.

1. Modelling electric vehicles use: a survey on the methods

2. Stochastic Optimal Energy Management of Smart Home With PEV Energy Storage

3. Power market equilibrium considering an EV storage aggregator exposed to marginal prices - A bilevel optimization approach

4. Integrated Energy Exchange Scheduling for Multimicrogrid System With Electric Vehicles

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3. FMGCN: Federated Meta Learning-Augmented Graph Convolutional Network for EV Charging Demand Forecasting;IEEE Internet of Things Journal;2024-07-15

4. Hybrid CNN-LSTM Forecasting Model for Electric Vehicle Charging Demand in Smart Buildings;2024 6th Global Power, Energy and Communication Conference (GPECOM);2024-06-04

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